Data science and decision science are two data-driven fields that have grown in prominence over the past few years. Data scientists use data to come up with conclusions or predictions about things like customer behavior, while decision scientists combine data with other information sources to make decisions. The difference between data science and decision science is important for business owners who want to make informed decisions. In this post, you will learn about the difference between data science and decision science. Those venturing out to learn data science must understand whether they want to learn data science or decision science or both. The following are some of the key questions in relation to understanding the concepts related to data science and decision science.
- What is data science & decision science?
- When do we need data and decision science as part of the analytics strategy?
- Are there specialized courses for decision science?
- What are some good websites for decision sciences?
Table of Contents
What is Data Science & Decision Science?
Decision science is defined as a field of study that combines data, data analysis, and other data sources to make decisions. The field of decision science has long been known as operations research or management science. Using data for decision-making can be useful because it helps understand customer behavior and make data-driven decisions. Decision Sciences is an interdisciplinary field that draws on applied probability, economics, operations research, machine learning, statistical decision theory, forecasting, and cognitive psychology. Decision sciences provide tools and analytics methods/techniques using which managers can improve on decision making. These techniques range from sharpening statistical intuition to quantitative decision analysis. The following are some of the research areas in the field of decision sciences:
- Decision making under uncertainty
- Individual and group decision making
- Optimized decision making using Machine learning & AI
Data science is a wide field that includes data gathering, data analysis, data visualization, and decision making to help businesses understand their customers better. Data scientists use statistical techniques and machine learning to analyze large volumes of data in order to discover patterns, draw conclusions, or predict future outcomes based on data.
While Data science is used to extract insights from the data after performing data preparation activities, decision science helps make the decision based on the insights with an aim to solve business problems. Decision science integrates analytical and behavioral approaches to decision-making. Decision science depends on data science to extract insights from the data. The decision science field integrates and builds upon data sciences by adding business context, design thinking, and behavioral sciences.
Data scientists look at the data to extract insights and build models of high accuracy without caring much overall impact on business outcomes. However, decision scientists see data as a tool to make decisions. For decision scientists, the business problem is of paramount importance. Unlike data scientists, decision scientists need to have both business acumen and analytical ability.
The must-have skills for a decision scientist include data analysis, data visualization, and data mining. In order to be a successful decision scientist, it is also important to have strong communication skills so you can effectively communicate findings from data analysis with others in the company. Decision science allows organizations to make well-informed decisions using data analytics which helps businesses become more efficient and effective.
When do we go for data and decision sciences as part of analytics strategy?
In a complex business environment, where improved decision-making could impact the business in a positive manner, it will be good to have both data science and decision science teams. Decision scientists will work with data scientists to help managers make better decisions resulting in positive business outcomes.
As a matter of fact, it will be good to have all of the following teams as part of a solid analytics strategy:
- Data engineering team: Helps with data processing
- Data sciences team: Helps with extracting insights in relation to business problems
- Decision sciences team: Helps with better and optimal decison making
Decision scientists use data to make decisions, while data scientists gather data and perform analysis in order to come up with conclusions or predictions about things like customer behavior. Data scientists rely on large volumes of data that they analyze using statistical techniques and machine learning, which is not always available.
Decision scientists are rarer than data scientists as they blend business, math, technology, and behavioral science and are “both precise and good with communication.”
Are there specialized courses for Decision Sciences?
Here are some links which could take you to specialized courses for decision sciences:
- Decision Science (BS) from CMU: Decision science major from CMU covers the following topics:
- Normative analysis, creating formal models of choice
- Descriptive research, studying how cognitive, emotional, social, and institutional factors affect judgment and choice
- Prescriptive interventions, seeking to improve judgment and decision making.
- Decision Sciences from IIM Bengaluru: Decision sciences course is offered as a specialization course under the Doctor of Philosophy (Ph.D.) program from IIM Bengaluru. The course covers lectures on operation research (OR) methods, statistical methods including Bayesian and multivariate statistics, time-series forecasting, etc.
- Decision sciences from INSEAD
- Decision science-related courses from Coursera: There are several courses from Coursera which are related to data-driven decision making. Some of them are the following:
What are some good websites for Decision Sciences?
Here are some good websites for decision sciences:
- Decision science journal
Here is a great video from chief decision scientist of Google, Dr. Cassie Kozyrkov
- Difference between Data Science & Decision Science – November 3, 2021
- OKRs vs KPIs: Differences and Examples – November 2, 2021
- Free Python & R Training from Spoken Tutorial Initiative – November 1, 2021
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